Runs with different selectivity assumptions where:
- base: selectivity at age allowed to vary (sigma
penalty=0.7)
- high: selectivity at age constrained (sigma
penalty=0.05)
- mod: selectivity at age moderately constrained (sigma
penalty=0.4)
- mix: selectivity at age moderately constrained for
middle ages, high for older ages, loose for younger ages
---
title: "EBS pollock models"
author: "Ianelli"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
vertical_layout: fill
theme:
version: 4
bootswatch: minty
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
library(flexdashboard)
library(plotly)
library(r4ss)
library(tidyverse)
library(here)
library(ggridges)
getwd()
loadup<-FALSE
if (loadup){
source("GetResults.R")
r1 <- ss_run<-SS_obj()
ra <- SS_obj(SS_output(dir = here("ss","noramp"),verbose=FALSE),src="noramp")
r2 <- SS_obj(SS_output(dir = here("ss","mod")),src="mod")
r3 <- SS_obj(SS_output(dir = here("ss","mix")),src="mix")
r4 <- SS_obj(SS_output(dir = here("ss","high")),src="high")
#r5 <- SS_obj(SS_output(dir = here("ss","autocor")),src="autocor")
ss_sel <- rbind(r1$sel,r2$sel,r3$sel,r4$sel)#,r5$sel)
#compute_matrix_summary(sel[,2:16])
gp_run<-gp_obj()
am_run<-AMAK_obj()
pm_run<-pm_obj()
load(here("SAM","poll23","run","model2.RData"))
sam_run <- SAM_obj()
all_sel <- rbind(sam_run$sel,pm_run$sel,am_run$sel,ss_run$sel,gp_run$sel)
all_ts <- rbind( sam_run$ts,pm_run$ts,am_run$ts,ss_run$ts,gp_run$ts)
} else {
load(here("compares.Rdata"))
}
```
Platforms
=======================================================================
Column {.tabset}
-----------------------------------------------------------------------
### Selectivity
```{r}
p<-Plot_Sel() + ggthemes::theme_few(base_size=11)
p
```
### Selectivity by age
```{r}
p <- Plot_Sel_age()
ggplotly(p)
```
### SSB
```{r}
p<- Plot_SSB()
ggplotly(p)
```
### Stock recruitment relationship
```{r}
p<- Plot_SRR()
ggplotly(p)
```
SS runs
=======================================================================
Column {.tabset}
-----------------------------------------------------------------------
### Run description
Runs with different selectivity assumptions where:
- **base**: selectivity at age allowed to vary (sigma penalty=0.7)
- **high**: selectivity at age constrained (sigma penalty=0.05)
- **mod**: selectivity at age moderately constrained (sigma penalty=0.4)
- **mix**: selectivity at age moderately constrained for middle ages, high for older ages, loose for younger ages
### Selectivity
```{r echo=FALSE}
ss_sel <- rbind(r1$sel,r2$sel,r3$sel,r4$sel)#,r5$sel)
p1 <- Plot_Sel(ss_sel)
p1
```
### Selectivity at age
```{r echo=FALSE}
p1 <- Plot_Sel_age(ss_sel)
ggplotly(p1)
```
### SSB and recruitment
```{r echo=FALSE}
ss_ts <- rbind(r1$ts,r2$ts,r3$ts,r4$ts)#,r5$sel)
p1 <- Plot_SSB(ss_ts)
ggplotly(p1)
```
With and w/o ramp
=======================================================================
### SSB and recruitment
```{r, echo=FALSE, warning=FALSE, message=FALSE}
# Get results w/ and w/o ramp
df <- rbind(r1$ts,ra$ts)
p1 <- df |> filter(Year<2024,Year>1953) |> ggplot(aes( x=Year, y= value,color=source)) +
geom_line(stat='identity') + geom_point(stat='identity') +
ggthemes::theme_few() + ylab("SSB") + xlab("Year") +
ylim(0,NA) + facet_grid(type~.,scales="free_y")
ggplotly(p1)
```